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Does Intuitionistic Fuzzy Analytic Hierarchy Process Work Better Than Analytic Hierarchy Process?

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Abstract

Analytical hierarchy process (AHP) has been prevailing in multicriteria decision-making (MCDM) problems. Meanwhile, the fuzzy sets family has shown great power in representing vagueness and advancing the decision quality under uncertainties. The literature well documented the foundation and advantages of their integration, such as Fuzzy AHP. However, under what conditions do such integrations surely perform better than AHP in the MCDM process is still unclear. In this paper, we pick intuitionistic fuzzy (IF) sets—one of the advanced and most prevailing members of the fuzzy sets family, and further investigate when and how to integrate IF and AHP (IF-AHP) to the best advantage. We illustrate the formulated quantitative differences between the weight of AHP and the normalized defuzzified weight of IF-AHP. We uncover the qualitative and quantitative differences between AHP and IF-AHP, and identify the conditions and strategies of using IF-AHP instead of AHP. We use data experiments to illustrate our findings and further implement two case studies based on the real scenarios of supplier selection for validation and explanation.

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References

  1. Chai, J., Ngai, E.W.T.: Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Application. 140, 112903 (2021).

  2. Chai, J., Liu, J.N.K., Ngai, E.W.T.: Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Application. 40(10), 3872–3885 (2013)

    Article  Google Scholar 

  3. Xu, Z.S., Liao, H.: Intuitionistic fuzzy analytic hierarchy process. IEEE Trans. Fuzzy Syst. 22(4), 749–761 (2014)

    Article  Google Scholar 

  4. Chan, H.K., Sun, X., Chung, S.: When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems. 125, 113114 (2019).

  5. Chai, J., Liu, J.N.K.: A novel believable rough set approach for supplier selection. Expert Syst. Appl. 41(1), 92–104 (2014)

    Article  Google Scholar 

  6. Chai, J., Ngai, E.W.T.: Multi-perspective strategic supplier selection in uncertain environments. Int. J. Prod. Econ. 166, 215–225 (2015)

    Article  Google Scholar 

  7. Chai, J., Liu, J.N.K., Xu, Z.S.: A new rule-based SIR approach to supplier selection under intuitionistic fuzzy environments. Internat. J. Uncertain. Fuzziness Knowledge-Based Systems 20(3), 451–471 (2012)

    Article  Google Scholar 

  8. Chai, J., Liu, J.N.K., Xu, Z.S.: A rule-based group decision model for warehouse evaluation under IVIF environments. Expert Syst. Appl. 40(6), 1959–1970 (2013)

    Article  Google Scholar 

  9. Saaty, T.L.: Axiomatic foundation of the analytic hierarchy process. Manage. Sci. 32(7), 841–855 (1986)

    Article  MathSciNet  Google Scholar 

  10. Wind, Y., Saaty, T.L.: Marketing applications of the analytic hierarchy process. Manage. Sci. 26(7), 641–658 (1980)

    Article  Google Scholar 

  11. Nag, K., Helal, M.: Multicriteria inventory classification of diabetes drugs using a comparison of AHP and fuzzy AHP models. In the Proceeding of the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 1456–1460 (2018).

  12. Supriya, M., Sangeeta, K., Patra, G.K.: Comparison of AHP based and fuzzy based mechanisms for ranking cloud computing services. In the Proceeding of the 2015 International Conference on Computer, Control, Informatics, and its Applications (IC3INA), 175–180 (2015).

  13. Mosadeghi, R., Warnken, J., Tomlinson, R., Mirfenderesk, H.: Comparison of fuzzy-AHP and AHP in a spatial multicriteria decision making model for urban land-use planning. Comput. Environ. Urban Syst. 49, 54–65 (2015)

    Article  Google Scholar 

  14. Zhu, B., Xu, Z.S.: Analytic hierarchy process-hesitant group decision making. Eur. J. Oper. Res. 239(3), 794–801 (2014)

    Article  MathSciNet  Google Scholar 

  15. Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20, 87–96 (1986)

    Article  Google Scholar 

  16. Szmidt, E., Kacprzyk, J.: Distances between intuitionistic fuzzy sets. Fuzzy Sets Syst. 114(3), 505–518 (2000)

    Article  MathSciNet  Google Scholar 

  17. Xu, Z.S., Yager, R.R.: Some geometric aggregation operators based on intuitionistic fuzzy sets. Int. J. Gen Syst 35(4), 417–433 (2006)

    Article  MathSciNet  Google Scholar 

  18. Xu, Z.S.: Intuitionistic fuzzy aggregation operators. IEEE Trans. Fuzzy Syst. 15(6), 1179–1187 (2007)

    Article  Google Scholar 

  19. Xu, Z.S.: Intuitionistic preferences relations and their application in group decision making. Inf. Sci. 177(11), 2363–2379 (2007)

    Article  MathSciNet  Google Scholar 

  20. Xu, M., Liu, S., Xu, Z.S., Zhou, W.: DEA evaluation method based on interval intuitionistic bayesian network and its application in enterprise logistics. IEEE Access. 98277–98289 (2019).

  21. Zhou, W., Xu, Z.S.: Envelopment analysis, preference fusion, and membership improvement of intuitionistic fuzzy numbers. IEEE Trans. Fuzzy Syst. 28(9), 2119–2130 (2020)

    Article  Google Scholar 

  22. Nie, M., Tan W.W.: Towards an efficient type-reduction method for Interval Type-2 fuzzy logic systems. In the Proceeding of IEEE International Conference on Fuzzy Systems. 1425–1432 (2008).

  23. Runkler, T.A., Chen, C., John, R.: Type reduction operators for interval type–2 defuzzification. Inf. Sci. 467, 464–476 (2018)

    Article  MathSciNet  Google Scholar 

  24. Karnik, N.N., Mendel, J.M.: Centroid of a type-2 fuzzy set. Inf. Sci. 132, 195–220 (2001)

    Article  MathSciNet  Google Scholar 

  25. Mendel, J.M., Liu, F.: Super-exponential convergence of the Karnik-Mendel algorithms for computing the centroid of an interval type-2 fuzzy set. IEEE Trans. Fuzzy Syst. 15, 309–320 (2007)

    Article  Google Scholar 

  26. Chan, F.T.S., Kumar, N.: Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35(4), 417–431 (2007)

    Article  Google Scholar 

  27. Taherdoost, H., Brard, A.: Analyzing the process of supplier selection criteria and methods. Procedia Manufacturing. 32, 1024–1034 (2019)

    Article  Google Scholar 

  28. Chang, D.Y.: Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res. 95(3), 649–655 (1996)

    Article  Google Scholar 

  29. Mikhailov, L., Tsvetinov, P.: Evaluation of services using a fuzzy analytic hierarchy process. Appl. Soft Comput. 5(1), 23–33 (2004)

    Article  Google Scholar 

  30. Spiliotis, M., Skoulikaris, C.: A fuzzy AHP-outranking framework for selecting measures of river basin management plans. 167, 398–411 (2019)

    Google Scholar 

  31. Wu Z., Jiang B., Karimi R.H.: A logarithmic descent direction algorithm for the quadratic knapsack problem. Applied Mathematics and Computation. 369, 124854 (2020).

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Acknowledgements

We thank the editor and four anonymous reviewers for their constructive comments that have helped to improve the paper significantly. This study is supported financially in part by College Research Grant of BNU-HKBU United International College.

Funding

College Research Grant of BNU-HKBU United International College under No. 202026.

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Authors and Affiliations

  1. Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore

    Xiaofeng Chen

  2. AI & Digital Media Concentration of Arts in Communication, BNU-HKBU United International College, Zhuhai, China

    Yanting Fang

  3. Division of Business and Management, BNU-HKBU United International College, Zhuhai, China

    Junyi Chai

  4. Centre for Evaluation Studies, Beijing Normal University, Zhuhai, China

    Junyi Chai

  5. Business School, Sichuan University, Chengdu, China

    Zeshui Xu

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  1. Xiaofeng Chen
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  2. Yanting Fang
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  3. Junyi Chai
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  4. Zeshui Xu
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Correspondence to Junyi Chai.

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Chen, X., Fang, Y., Chai, J. et al. Does Intuitionistic Fuzzy Analytic Hierarchy Process Work Better Than Analytic Hierarchy Process?. Int. J. Fuzzy Syst. 24, 909–924 (2022). https://doi.org/10.1007/s40815-021-01163-1

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